Objective:
Fruit tree stakeholders have identified the need for effective, consistent control measures for apple postharvest physiological disorders and the development of additional control and management tools to replace or amend existing programs. Metabolic and genetic biomarker-based tools that are cost-effective will be developed under this project to predict, diagnose, and distinguish postharvest necrotic disorders to assure that high quality, disorder-free product remain available across the supply chain. Implementation of biomarker-based diagnostic tools represents a pragmatic, technology-driven shift from the treatment-based apple storage of the present to more economically feasible, sustainable, management-based systems, similar to those effectively applied in orchard systems such as integrated pest management.

Approach:
Our scientific approach applies metabolic and gene expression profiling to discover biomarkers that can be used to predict, diagnose, and distinguish economically significant apple postharvest physiological disorders. We will use this information to develop prototype predictive and diagnostic storage management tools and to re-evaluate prior understanding of disease classification based on distinguishing biomarkers. To demonstrate the economic feasibility of biomarker-based disorder management, the costs and benefits of biomarker-based tools will be compared with treatment-based tools alone or in combination. Long-term net benefits of each system will be simulated under various regional and policy environments to provide a range of plausible economic outcomes for stakeholders across the supply chain.